# gaiadr3_zeropoint
This Python package contains the necessary tools to query the value of the parallax zero-point for Gaia EDR3 and
Gaia DR3. Based on the functions described in Lindegren et al. 2020, the code returns the estimated parallax zero
-point given the ecliptic latitude, magnitude and colour of any Gaia (E)DR3 source.
**NOTE**: the zero-point returned by the code should be **subtracted** from the parallax value given in the Gaia archive. Run `help(zpt.get_zpt)` for more details.
## Documentation
All classes and methods/functions are documented so use the python help() function to find out more.
## Installation
This is a Python3 package (*issues may arise if executed with Python2*).
The required dependencies are:
* [numpy](https://numpy.org/)
* [pandas](https://pandas.pydata.org/) (only if you want to use the wrapper provided with the code)
To install the package:
### From source (recommended)
1. Clone the Github repository or download the source files
2. cd to the directory
3. Run `python setup.py install` or `python setup install --user` for installation in your own home directory
### With pip
```
pip install gaiadr3-zeropoint
```
## Basic usage
Once the package is installed, you can import it in Python:
```
from zero_point import zpt
```
Then, first load the coefficient tables by calling the `load_tables()` function.
Once the tables are loaded, the
parallax zero-point can be queried as:
```
zpt.get_zpt(phot_g_mean_mag, nu_eff_used_in_astrometry, pseudocolour, ecl_lat, astrometric_params_solved)
```
This function accepts both single values as well as iterables, and returns a float (or array of such) corresponding to the zero-point of the source(s) with those parameters.
**NOTE**: for 5-p solutions (ra-dec-parallax-pmra-pmdec), the field `astrometric_params_solved` equals 31 and the
`pseudocolour` variable can take any arbitrary values (even *None*). On the other hand, for 6-p solutions (ra-dec
-parallax-pmra-pmdec-pseudocolour), the field `astrometric_params_solved` equals 95 and the
`nu_eff_used_in_astrometry` variable can take any arbitrary values (even *None*).
Finally, if you have a pandas DataFrame (DF) of sources with the columns `phot_g_mean_mag, nu_eff_used_in_astrometry, pseudocolour, ecl_lat, astrometric_params_solved`, you can simply use the pandas wrapper ```zpt_wrapper```:
```
zero_point = DF.apply(zpt_wrapper,axis=1)
```
## Attribution
If you make use of this package for your research, please acknowledge the following papers: Lindegren+20.
## Help
If you encounter any problem with the software, please make use of the GitLub Issues page. Otherwise, contact pau.ramos@nao.ac.jp.
Copyright: Pau Ramos, University of Barcelona
Raw data
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"description": "# gaiadr3_zeropoint\n\nThis Python package contains the necessary tools to query the value of the parallax zero-point for Gaia EDR3 and\n Gaia DR3. Based on the functions described in Lindegren et al. 2020, the code returns the estimated parallax zero\n -point given the ecliptic latitude, magnitude and colour of any Gaia (E)DR3 source.\n\n **NOTE**: the zero-point returned by the code should be **subtracted** from the parallax value given in the Gaia archive. Run `help(zpt.get_zpt)` for more details.\n\n## Documentation\n\nAll classes and methods/functions are documented so use the python help() function to find out more. \n\n\n## Installation\n\nThis is a Python3 package (*issues may arise if executed with Python2*).\n\nThe required dependencies are:\n* [numpy](https://numpy.org/)\n* [pandas](https://pandas.pydata.org/) (only if you want to use the wrapper provided with the code)\n\n\nTo install the package:\n\n### From source (recommended)\n1. Clone the Github repository or download the source files\n2. cd to the directory\n3. Run `python setup.py install` or `python setup install --user` for installation in your own home directory\n\n### With pip\n```\npip install gaiadr3-zeropoint\n```\n\n\n## Basic usage\n\nOnce the package is installed, you can import it in Python:\n\n```\nfrom zero_point import zpt\n```\n\nThen, first load the coefficient tables by calling the `load_tables()` function. \n\nOnce the tables are loaded, the\n parallax zero-point can be queried as:\n\n```\nzpt.get_zpt(phot_g_mean_mag, nu_eff_used_in_astrometry, pseudocolour, ecl_lat, astrometric_params_solved)\n```\n\nThis function accepts both single values as well as iterables, and returns a float (or array of such) corresponding to the zero-point of the source(s) with those parameters.\n\n**NOTE**: for 5-p solutions (ra-dec-parallax-pmra-pmdec), the field `astrometric_params_solved` equals 31 and the\n `pseudocolour` variable can take any arbitrary values (even *None*). On the other hand, for 6-p solutions (ra-dec\n -parallax-pmra-pmdec-pseudocolour), the field `astrometric_params_solved` equals 95 and the\n `nu_eff_used_in_astrometry` variable can take any arbitrary values (even *None*).\n\nFinally, if you have a pandas DataFrame (DF) of sources with the columns `phot_g_mean_mag, nu_eff_used_in_astrometry, pseudocolour, ecl_lat, astrometric_params_solved`, you can simply use the pandas wrapper ```zpt_wrapper```:\n\n``` \nzero_point = DF.apply(zpt_wrapper,axis=1) \n```\n\n## Attribution\n\nIf you make use of this package for your research, please acknowledge the following papers: Lindegren+20.\n\n## Help\n\nIf you encounter any problem with the software, please make use of the GitLub Issues page. Otherwise, contact pau.ramos@nao.ac.jp.\n\nCopyright: Pau Ramos, University of Barcelona\n\n",
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